2 Structure of the course

One session is meant to consist of 2 hour (max) lecture as well as a homework that takes about 30 - 60 minutes to complete.

Week Topic Description
1 Before you learn the language - Why learning R
- How to use R as a beginner
- Types of R files
- Ensuring reproducibility
- How to learn the language
2 Introduction to R - working directory demonstration
- objects in R
- functions and their arguments
- data types
- atomic vectors
- lists
- dataframes/tibbles
- subsetting vectors
3 Import data and how to work with dataframes - what are dataframes
- how to create dataframes
- basic properties of dataframes
- how to import and export data
- Selecting and filtering your data
- the pipe operator %>%
4 Data transformation, data summary, functions and conditional execution
- mutate
- summarise
- group_by
- write your own functions
- use if/else statements
5 Working with strings (characters) - manipulate strings
- regex basics
- find/extract/replace matched strings
6 ggplot2 basics and Iteration - grammar of graphics
- scatterplot with regression line
- for loops
- while loops
- map function
7 ggplot2 - scatterplots
- linegraphs
- boxplots
- histograms
- barplots
8 Using Rmarkdown for scientific reporting - What is Rmarkdown
- Why bother learning it?
- Hands-on